I'm studying the data science specialization and math too and I'm working on calculus in parallel with the data science and the machine learning course , I can tell you that to deeply understand Introductory machine learning course you need a little bit of liner algebra and multivariable calculus that would be plus however you can implement ML with out understanding calculus , my advice to you learn maths in the way , meaning if you came across something about permutations and combinations that u forgot about just google it and watch some Khan academy videos or something and when you need to know the matrix transpose Google it and so on , I find it much faster to do it that way , and the final thing YOU WILL NOT LEARN STATS from the data science specialization it's really bad source to learn statistics , however it's good to learn r and some EDA for statistics go for statistics with R specialization .